Digital Agenda for Europe
A Europe 2020 Initiative

Internet of Services Collaboration

Experimental Awareness of CO2 in Federated Cloud Sourcing

Ecological implications of the rapid proliferation of Cloud-based IT infrastructures form an important gap in the current state of the art in both research and practice. Addressing this gap is vital for sustainable future developments in Cloud computing. In this respect, ECO2Clouds aims to investigate strategies that can ensure not only effective application deployment on the Cloud infrastructure but also reduce the resultant energy consumption and CO2 emissions.

The need for novel deployment strategies becomes more evident when an application spans multiple Clouds. Furthermore, Cloud providers operate under different regulatory frameworks and cost structures in relation to environmental policies and energy value-chains. Thus, optimising the way key assets such as application logic and databases are deployed is constrained by a set of non-functional requirements such as quality, privacy and cross-platform, service-level agreements.

To date, little is known about how to incorporate Carbon emissions and energy consumption into application development and deployment decision models. ECO2Clouds will provide a timely, challenging and highly innovative approach to Cloud computing service delivery, which will tackle the following issues:

• Develop Cloud application programming interface extensions and mechanisms to collect eco-metrics at infrastructure and VM level, and quantify the environmental impact of execution at infrastructure and application level

• Investigate the key environment, quality and cost parameters needed so as to underpin a holistic approach to multi-Cloud application deployment

• Develop evaluation mechanisms and optimization algorithms to assess different parameter configurations and their influence in energy-efficient Cloud sourcing and application-deployment strategies

• Integrate the Carbon-aware mechanisms into an existing FIRE facility so as to test, validate and optimize the eco-metrics, models and algorithms developed.

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